C.06 Surgical resection of pediatic posterior fossa tumours in the molecular era
Bibliographic record
Abstract
Background: Aggressive surgical resections of posterior fossa tumours result in tremendous neurological sequelae as a result of damage to the brainstem. As such we sought to re-evaluate the role of aggressive surgical resections in the molecular era. Methods: 820 posterior fossa ependymoma and 787 medulloblastoma were genomically profiled and correlated with pertinent clinical variables. Results: Across 787 medulloblastoma cases, the value of extent of resection was greatly dampened when accounting for molecular subgroup. Near-total resections are equivalent to gross total resections across all four subgroups even when correcting for treatment. The prognostic value of a gross total resection as compared to a subtotal resection (>1.5cm2 residual) was restricted to Group 4 tumours (HR 1.26). Across 820 posterior fossa ependymoma PFA ependymoma was a very high risk group compared to PFB ependymoma, and a subtotal PFA ependymoma conferred an extremely poor prognosis. Gross totally resected PFB ependymoma could be cured with surgery alone. Prognostic nomograms in both medulloblastoma and ependymoma revealed molecular subgroup to be the most important predictor of outcome. Conclusions: The prognostic benefit of EOR for patients with medulloblastoma is marginal after accounting for molecular subgroup affiliation. In both molecular subgroups of posterior fossa ependymoma, gross total resection remains an important predictor of outcome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".